Kerry Back
a*b*c, a**3, etc.pipe.predict, it will enlarge the feature set in the same way and then predict using the trained model.from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import make_column_transformer
from sklearn.pipeline import make_pipeline
transform = make_column_transformer(
(OneHotEncoder(), ["industry"]),
remainder="passthrough"
)
poly = PolynomialFeatures(degree=2, include_bias=False)
pipe = make_pipeline(
transform,
poly,
model
)